Good Governance in the “Oil Sector” and its Effect on Economic Development: A Case Study of the Kurdistan Region of Iraq
Bibliographic record
Abstract
International development agencies demand good governance of natural resources in developing resource abundant countries similar to developed resource-rich countries such as Norway, Canada, and the United States.Governance of the extractive industry sector has become the main concern for the international community since the 1970s.In this regard, governance of natural resource sector codes is a serious challenge for nations and governments especially in developing resource abundant countries.Accordingly, resource rich countries' economic prosperity heavily depends on extractive natural resources including, oil, gas, coal, copper, diamonds etc.Similar to that the Kurdistan Region depends on oil as the key commodity for its economy.This thesis takes into account the oil sector in the Kurdistan Region of Iraq and the implementation of the key principles of good governance of the natural resource sector in pursuing sound economic development for the region.The dynamics of oil governance are fraught with wicked challenges regionally and globally for the Kurdistan Region, the natural resource sector has different peculiarities, which might be different from other sectors of the economy.Therefore, being a resource dependent economy means having a volatile economy with high predictability of economic crisis and growth decline.Considering these circumstances, this study has been designed to analyze good governance principles based on international standards of governance.For this purpose the Natural Resource Charter Precepts will assist the KRG in investing revenues from the oil sector for sustainable development, and economic competitiveness.Approaching to achieve full sustainability from "natural capital" requires the oil industry of the region to be internationalized and regionalized, that means shifting to acquire a model for the oil sector which is viable in economic terms for the Kurdistan Region.The KRG has to put priority for better governance of the oil sector as the key variable for economic growth.To comply with this the research seeks to find possible ways that contribute to better governance of the oil sector.The nature of this study tackles both the good governance perspective and economic development.That is to track the effect of good governance in the economic development of the region depending only on oil.For building a comprehensive horizon of governance that is transparent and accountable to the public and international community.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".